Explore MATLAB source code curated for "最优化算法" with clean implementations, documentation, and examples.
This MATLAB example program demonstrates mathematical numerical processing techniques, including optimization algorithms and related implementations. The code is provided for shared academic use only - commercial applications are strictly prohibited. Thank you for respecting these terms.
Self-developed MATLAB optimization algorithms including Golden Section (0.618) method, Gradient Descent, Conjugate Gradient, and Penalty Function approaches with detailed implementation code and algorithmic explanations.
A comprehensive MATLAB-based graphical interface for solving arbitrary Linear Programming (LP) problems using optimization algorithms including Simplex Method, Two-Phase Method, Big M Method, and Dual-Phase Simplex Method. The implementation features constraint matrix handling, tableau operations, pivot element selection, and real-time solution visualization with step-by-step iteration tracking.
MATLAB-based optimization algorithm implementation featuring the classic Powell method - an excellent program with clean, understandable code for nonlinear minimization problems
A comprehensive image registration toolkit featuring: 1) GUI interface with proj.m image selection window and testListBoxlj.m, 2) Optimization algorithms PSO.m and POWELL.m, 3) Mutual information metrics MI.m, EMI.m, RMI.m, HiMI.m, GMI.m, FPMI.m, 4) POWELL subprogram oneDimSearch.m, 5) PSO subprogram myMI.m, 6) Registration validation program restore.m, 7) Image transformation tool gobad.m for translation and rotation operations.
Complete MATLAB source code for the Gauss-Newton optimization algorithm with detailed implementation examples and application scenarios.
Optimization algorithms including Conjugate Gradient, Newton's Method, Golden Section Search, and Steepest Descent methods with implementation insights
MATLAB source code for conjugate gradient optimization algorithm with detailed implementation notes.
MATLAB implementation of the optimized BFGS algorithm for unconstrained optimization problems
Shared genetic algorithm code developed through years of research! Implements optimization algorithms with fitness functions, selection methods, crossover operations, and mutation mechanisms for solving complex problems.